📚 Related Theory Notes
💻 Hands-on practice (All codes will be provided to participants 🔜)
| Day 1: 07.10.2024 | Introduction | |
| 9:00 - 10:45 | Introduction to GEE for Big Data Analysis | 📚Big Data 🔸Big Data 🔸Geospatial Big Data 🔸Cloud Computing 📚Google Earth Engine (GEE) 🔸What is GEE? 🔸Why GEE? 🔸How to Access? |
| 10:45 - 11:00 | Short Break | Make sure everyone has an GEE account before the practice session! |
| 11:00 - 13:00 | Getting started with GEE | 💻 The Google Earth Engine Interface 💻 JavaScript Basic in GEE 📝 Tips & Learning resources |
| 13:00 - 14:00 | Lunch time | |
| 14:00 - 16:00 | Hands-on practice | 💻 Exploring GEE Data Catalog Raster 🔸Select imagery using Image ID in the GEE data catalog 🔸Select imagery (images) from ee.ImageCollection Vector 🔸Geometry 🔸Feature 🔸Feature Collection 💻Import data to GEE (avaiable in “Data” session) 💻Export data from GEE |
| Day 2: 08.10.2024 | Data Management, Analysis, and Applications | |
| 9:00 - 10:45 | Data Management and Analysis in GEE | 📚A very brief introduction 💻 Calculating Image Indices 💻 Cloud Masking 💻 Image Composition |
| 10:45 - 11:00 | Short Break | |
| 11:00 - 13:00 | Land Cover Classification | 📚A very brief introduction 🔸Machine Learning in GEE 🔸Supervised Land Cover Classification |
| 13:00 - 14:00 | Lunch time | |
| 14:00 - 16:00 | Hands-on practice | 💻 Land Cover Classification: 1️⃣ Select Area of Interest 2️⃣ Prepare input Data (Satellite Data, Auxiliary Data) 3️⃣ Prepare Training and Validation Samples Additional Task : Optimizing input data for LUC |
| Day 3: 09.10.2024 | Data Management, Analysis, and Applications (cont.) | |
| 9:00 - 10:45 | Hands-on practice | 💻 Land Cover Classification (Cont.) 4️⃣ Apply ML Classifier (e.g., Random Forest) 5️⃣ Accuracy Assessment |
| 10:45 - 11:00 | Short Break | |
| 11:00 - 13:00 | Explore the LUC results | 📝 Discussing the classification results 📝 Lesson Learned, Tricks, and Tips for better LUC Results |
| 13:00 - 14:00 | Lunch time | |
| 14:00 - 15:30 | Time series analysis & Applications | 💻 Spatiotemporal Data & Analysis in GEE 📝 Time series Application |
| 15:30 - 16:00 | Wrap-Up & Remark | 📝Maximize GEE Applications 📝Further explore GEE |